TY - JOUR
T1 - Testing a Model of Destination Image Formation
T2 - Application of Bayesian Relational Modelling and fsQCA
AU - Kano Glückstad, Fumiko
AU - Schmidt, Mikkel Nørgaard
AU - Mørup, Morten
N1 - Published online: 25 November 2019
PY - 2020/11
Y1 - 2020/11
N2 - Individuals’ destination images are constantly updated through their exposure to various stimuli sent from diverse information sources1 widely accessible in the modern society. Such dynamics of destination image formation2 is better explained with the iterative process of a concept learning framework integrated into the destination image models. DDIF implies that individuals having been exposed to similar stimuli in the iterative image formation process have a higher likelihood of developing a similar mental representation3. Accordingly, this study employs an innovative methodological framework to extract patterns of MR of destinations held by groups of individuals (segments) and to compare segment-specific patterns of MR with their relations to willingness to visit4 and to ISs. The results demonstrate that what segments associate with a destination relates to their W2V, and segments having rich and positive associations with a destination accessed a wider range of ISs to learn about the destination.
AB - Individuals’ destination images are constantly updated through their exposure to various stimuli sent from diverse information sources1 widely accessible in the modern society. Such dynamics of destination image formation2 is better explained with the iterative process of a concept learning framework integrated into the destination image models. DDIF implies that individuals having been exposed to similar stimuli in the iterative image formation process have a higher likelihood of developing a similar mental representation3. Accordingly, this study employs an innovative methodological framework to extract patterns of MR of destinations held by groups of individuals (segments) and to compare segment-specific patterns of MR with their relations to willingness to visit4 and to ISs. The results demonstrate that what segments associate with a destination relates to their W2V, and segments having rich and positive associations with a destination accessed a wider range of ISs to learn about the destination.
KW - Destination image formation
KW - Mental representation
KW - Concept learning
KW - Segmentation
KW - fsQCA
KW - Nonparametric Bayesian relational modelling
KW - Destination image formation
KW - Mental representation
KW - Concept learning
KW - Segmentation
KW - fsQCA
KW - Nonparametric Bayesian relational modeling
U2 - 10.1016/j.jbusres.2019.10.014
DO - 10.1016/j.jbusres.2019.10.014
M3 - Journal article
SN - 0148-2963
VL - 120
SP - 351
EP - 363
JO - Journal of Business Research
JF - Journal of Business Research
ER -